论文标题
情感分析：从文本中自动检测价，情感和其他情感状态
Sentiment Analysis: Automatically Detecting Valence, Emotions, and Other Affectual States from Text
论文作者
论文摘要
机器学习的最新进展导致了类似人类行为的计算机系统。情感分析是文本中情绪的自动确定，使我们能够利用以前无法实现的商业，公共卫生，政府政策，社会科学和艺术的机会。此外，从新闻到社交媒体帖子中对文本中情绪的分析不仅在于我们对人们如何通过语言传达情感，还可以使情感如何塑造我们的行为的理解。本文介绍了情感分析研究的全面概述，其中包括：该领域的起源，任务的丰富景观，挑战，对所使用方法和资源的调查以及应用程序。我们还讨论了如何在没有仔细的预先思考的情况下如何产生有害结果的潜力。我们概述了在情感分析中追求公平性的最新研究线。
Recent advances in machine learning have led to computer systems that are human-like in behaviour. Sentiment analysis, the automatic determination of emotions in text, is allowing us to capitalize on substantial previously unattainable opportunities in commerce, public health, government policy, social sciences, and art. Further, analysis of emotions in text, from news to social media posts, is improving our understanding of not just how people convey emotions through language but also how emotions shape our behaviour. This article presents a sweeping overview of sentiment analysis research that includes: the origins of the field, the rich landscape of tasks, challenges, a survey of the methods and resources used, and applications. We also discuss discuss how, without careful fore-thought, sentiment analysis has the potential for harmful outcomes. We outline the latest lines of research in pursuit of fairness in sentiment analysis.
